Open AccessTADBD: a sensitive and fast method for detection of typologically associated domain boundaries
Author(s) -
Hongqiang Lyu,
Lin Li,
Zhiyong Wu,
Wei Tian,
Juan Zheng,
Hongda Wang
Publication year - 2020
Publication title -
biotechniques/biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/btn-2019-0165
Subject(s) - diagonal , boundary (topology) , haar , computer science , matrix (chemical analysis) , acceleration , domain (mathematical analysis) , block (permutation group theory) , scale (ratio) , algorithm , pattern recognition (psychology) , artificial intelligence , mathematics , physics , geometry , mathematical analysis , materials science , classical mechanics , quantum mechanics , wavelet , composite material
A topologically associated domain (TAD) is a self-interacting genomic block. Detection of TAD boundaries on Hi-C contact matrix is one of the most important issues in the analysis of 3D genome architecture at TAD level. Here, we present TAD boundary detection (TADBD), a sensitive and fast computational method for detection of TAD boundaries on Hi-C contact matrix. This method implements a Haar-based algorithm by considering Haar diagonal template, acceleration via a compact integrogram, multi-scale aggregation at template size and statistical filtering. In most cases, comparison results from simulated and experimental data show that TADBD outperforms the other five methods. In addition, a new R package for TADBD is freely available online.